This document provides an introduction and overview of Apache Camel, an open source framework for integrating applications and systems. It discusses how Camel implements common enterprise integration patterns (EIP) and uses a declarative domain-specific language to define routing and integration logic. Key concepts covered include Camel's architecture, components, endpoints, programming model, type conversion, error handling and hiding the Camel API from client code.
The document discusses various web technologies including HTML5, CSS, JavaScript, jQuery, ASP.NET, MVC pattern, and more. It provides an overview of each topic with definitions and examples. It also includes a brief history and future directions of web standards.
The document discusses advanced features of the AjaxTags Library including autocomplete textboxes that populate associated values in other textboxes. It provides an example of an autocomplete textbox that populates a secondary textbox with a linked Spanish word when an English animal is selected. The server-side code returns an XML list with names and values to map selections to the secondary field. Training courses are also advertised on Ajax, Java EE and other technologies.
This presentation will provide a history and overview of the field of Automatic Machine Learning (AutoML), followed by a detailed look inside H2O's AutoML algorithm. H2O AutoML provides an easy-to-use interface which automates data pre-processing, training and tuning a large selection of candidate models (including multiple stacked ensemble models for superior model performance). The result of the AutoML run is a "leaderboard" of H2O models which can be easily exported for use in production. AutoML is available in all H2O interfaces (R, Python, Scala, web GUI) and due to the distributed nature of the H2O platform, can scale to very large datasets. The presentation will end with a demo of H2O AutoML in R and Python, including a handful of code examples to get you started using automatic machine learning on your own projects.
The document provides an overview of the Prototype JavaScript framework and its support for Ajax functionality. It discusses topics like installing Prototype, the Ajax.Request, Ajax.Updater, and Ajax.PeriodicalUpdater objects, handling JSON data, and comparing Prototype's Ajax support to other libraries like jQuery, Dojo and Ext JS. It also provides examples of using Prototype for Ajax requests and updating HTML elements.
This presentation has been developed in the context of the Mobile Applications Development course, DISIM, University of L'Aquila (Italy), Spring 2016.
http://www.ivanomalavolta.com
This document provides an introduction to building web applications using the Jakarta Struts framework. It discusses some of the challenges of building web applications and how Struts addresses these challenges through its implementation of the MVC pattern. It provides an overview of Struts' controller, model, and view components and how they work together. It also presents a case study of building an online poll application with Struts to demonstrate these concepts. Key benefits of Struts like separation of components and reusability are highlighted. The document concludes with tips on getting started quickly with Struts.
UNIT – 4
PART I
APPLET
APPLETS - GUI COMPONENTS
APPLET PARAMETERS
LIFE CYCLE OF AN APPLET
APPLICATION CONVERSION TO APPLETS
AWT AND AWT HIERARCHY
SWING COMPONENTS
This document discusses Ajax and provides code examples for implementing basic Ajax functionality. It begins with an overview of Ajax and its motivation, then describes the basic Ajax process including defining a request object in JavaScript, initiating a request, and handling the response. It provides JavaScript and HTML code examples to send a GET request, handle the response, and display returned data.
The document discusses various web technologies including HTML5, CSS, JavaScript, jQuery, ASP.NET, MVC pattern, and more. It provides an overview of each topic with definitions and examples. It also includes a brief history and future directions of web standards.
The document discusses advanced features of the AjaxTags Library including autocomplete textboxes that populate associated values in other textboxes. It provides an example of an autocomplete textbox that populates a secondary textbox with a linked Spanish word when an English animal is selected. The server-side code returns an XML list with names and values to map selections to the secondary field. Training courses are also advertised on Ajax, Java EE and other technologies.
This presentation will provide a history and overview of the field of Automatic Machine Learning (AutoML), followed by a detailed look inside H2O's AutoML algorithm. H2O AutoML provides an easy-to-use interface which automates data pre-processing, training and tuning a large selection of candidate models (including multiple stacked ensemble models for superior model performance). The result of the AutoML run is a "leaderboard" of H2O models which can be easily exported for use in production. AutoML is available in all H2O interfaces (R, Python, Scala, web GUI) and due to the distributed nature of the H2O platform, can scale to very large datasets. The presentation will end with a demo of H2O AutoML in R and Python, including a handful of code examples to get you started using automatic machine learning on your own projects.
The document provides an overview of the Prototype JavaScript framework and its support for Ajax functionality. It discusses topics like installing Prototype, the Ajax.Request, Ajax.Updater, and Ajax.PeriodicalUpdater objects, handling JSON data, and comparing Prototype's Ajax support to other libraries like jQuery, Dojo and Ext JS. It also provides examples of using Prototype for Ajax requests and updating HTML elements.
This presentation has been developed in the context of the Mobile Applications Development course, DISIM, University of L'Aquila (Italy), Spring 2016.
http://www.ivanomalavolta.com
This document provides an introduction to building web applications using the Jakarta Struts framework. It discusses some of the challenges of building web applications and how Struts addresses these challenges through its implementation of the MVC pattern. It provides an overview of Struts' controller, model, and view components and how they work together. It also presents a case study of building an online poll application with Struts to demonstrate these concepts. Key benefits of Struts like separation of components and reusability are highlighted. The document concludes with tips on getting started quickly with Struts.
UNIT – 4
PART I
APPLET
APPLETS - GUI COMPONENTS
APPLET PARAMETERS
LIFE CYCLE OF AN APPLET
APPLICATION CONVERSION TO APPLETS
AWT AND AWT HIERARCHY
SWING COMPONENTS
This document discusses Ajax and provides code examples for implementing basic Ajax functionality. It begins with an overview of Ajax and its motivation, then describes the basic Ajax process including defining a request object in JavaScript, initiating a request, and handling the response. It provides JavaScript and HTML code examples to send a GET request, handle the response, and display returned data.
MSc Enterprise Systems Development Guest Lecture at UniS (2/12/09)Daniel Bryant
A guest lecture I presented to MSc Level Enterprise Systems Development students within the Department of Computing at the University of Surrey. This was a very similar presentation to the L2 lecture delivered the week earlier, but also included more advanced material.
Sling Models Using Sightly and JSP by Deepak KhetawatAEM HUB
This document discusses using Sling Models with Sightly and JSP templates in AEM. It provides an overview of Sling Models, including their purpose, design goals, and key annotations. It also describes the standard injectors available in Sling Models and how to create custom injectors. The document outlines how to add Sling Model dependencies and use Sling Models within JSP and Sightly templates, including code examples. It concludes with a demonstration of Sling Models in action and information for appendix materials and questions.
Spring is a lightweight, open-source application framework for Java. It uses dependency injection (DI) and inversion of control (IOC) to decouple application components. Spring's features include AOP, transaction management, JDBC support, and integration with various web frameworks like Struts and MVC. It supports DI through constructor injection and setter injection. Spring applications typically use XML configuration files to wire application components together.
This document discusses Sling Models, which provide a simplified way to adapt Sling resources into domain objects in AEM. Some key points:
- Sling Models allow resources to be adapted to POJOs with minimal code using annotations like @Model and @Inject. This is cleaner than previous "adapter factory" approaches.
- Common use cases like injecting resource properties, child resources, services and more are supported out of the box via standard injectors.
- Sling Models are pluggable, so custom injectors can be added to inject non-standard dependencies.
- They allow resources and requests to be adapted to either classes or interfaces, keeping domain objects simple POJOs.
The document discusses Java AWT event handling and graphics. It covers key concepts like events, event classes, event handling process, commonly used event listeners and adapter classes. It also covers AWT containers, layout managers, menu classes, graphics classes and how to work with frames and graphics in Java. The document is intended to teach programming in Java and is part of a larger unit on AWT.
This document discusses different options for navigating between task flows in an ADF application, including stack, network, hybrid, dashboard, and parallel navigation. It explains how each approach impacts memory usage, performance, and the user experience. Key factors like how task flows call or embed each other, and whether state is maintained or restored between flows, determine the tradeoffs of each approach. The document provides guidance to help developers choose a navigation strategy based on their specific requirements.
This document discusses Sling Models in AEM, including what they are, why they are useful, how to use them, and examples of Sling Model annotations. Sling Models allow mapping of Sling objects like resources and requests to plain Java objects using annotations. They reduce coding efforts and make code more maintainable by avoiding redundant code. The document covers the necessary dependencies, common annotations like @Model, @Inject, @Optional, and examples of injecting resources, child resources, and retrieving values from the request.
The document describes E-GEN iCAN, a tool for collecting, analyzing, and navigating production data in schedulers and z/OS environments. It provides an overview of the tool's interface and features, including its collectors, user interface, search engine, audit functionality, and client-server architecture. Use cases demonstrate how the tool can be used to generate run books, perform impact analysis, and enable quality assurance processes.
This document provides an overview of enterprise integration patterns (EIPs) and how they are implemented using Apache Camel and Project Fuji frameworks. It discusses core EIP principles like asynchronous messaging for integration. It also describes various EIP implementations like content-based routing, dead letter channels, and message transformation patterns. Code examples are shown using the Java and Spring DSLs for Apache Camel and the DSL and web UI for Project Fuji.
Real world #microservices with Apache Camel, Fabric8, and OpenShiftChristian Posta
What are, or aren't, microservices?
There's a lot of hype and buzz, but microservices emerged organically vs how some of the other distributed architectural styles were "handed down to us", so I believe there's some good things once you cut through the hype. In this talk I discussed what are and are NOT microservices, introduced some concepts, and discussed some concrete open-source libraries and frameworks that can help you develop and manage microservice style deployments.
Real-world #microservices with Apache Camel, Fabric8, and OpenShiftChristian Posta
What are and aren't microservices?
Microservices is a validation of the open-source approach to integration and service implementation and a rebuff of the committee-driven SOA approach. In this
The document discusses Apache Camel, an open source framework for integrating applications and building messaging endpoints. It provides an overview of Camel's capabilities including its lightweight nature, large number of components, support for various data formats, and use of Domain Specific Languages. Basic examples are shown using XML and Java DSLs. Key components, data formats, and Enterprise Integration Patterns supported by Camel are listed. Pros include its flexibility and large community, while documentation is listed as a con. Overall the document serves as an introduction to Apache Camel, outlining its main features and providing simple code examples.
Alfresco Business Reporting - Tech Talk Live 20130501Tjarda Peelen
This is the Slide Deck used in Alfresco's Tech Talk Live, May 1, 2013. It featured my Alfresco add-on: Alfresco Business Reporting. The purpose is to the technical 'why' and 'how' of the add-on module, the challenge faced and he solutions designed.
WebNet Conference 2012 - Designing complex applications using html5 and knock...Fabio Franzini
This document provides an overview of designing complex applications using HTML5 and KnockoutJS. It discusses HTML5 and why it is useful, introduces JavaScript and frameworks like KnockoutJS and SammyJS that help manage complexity. It also summarizes several JavaScript libraries and patterns including the module pattern, revealing module pattern, and MV* patterns. Specific libraries and frameworks discussed include RequireJS, AmplifyJS, UnderscoreJS, and LINQ.js. The document concludes with a brief mention of server-side tools like ScriptSharp.
This document provides an overview of ASP.NET MVC including its history, the MVC pattern, controllers, views, routing, and Razor views. It discusses the Model-View-Controller components, controller actions, action results, and action filters. It also covers view helpers, layouts, sections, and Razor syntax features.
Julien Simon "Scaling ML from 0 to millions of users"Fwdays
This document discusses scaling machine learning models from a single instance to millions of users. It begins by describing starting with a model on a local machine and then deploying it on a single EC2 instance. It notes the issues that arise with this approach as needs increase. It then discusses options for scaling to multiple instances, Docker clusters using ECS/EKS, and the fully managed SageMaker service. SageMaker is argued to require minimal effort for infrastructure and deployment compared to the other options as it scales models easily and focuses solely on machine learning tasks.
This document provides an overview of integrating microservices with Apache Camel and JBoss Fuse. It introduces Apache Camel as a lightweight integration library that uses enterprise integration patterns and domain-specific languages to define integration "flows" and "routes". It describes how Camel supports features like dynamic routing, REST APIs, backpressure, load balancing, and circuit breakers that are useful for building microservices. The document also introduces JBoss Fuse as a development and runtime platform for microservices that provides tooling, frameworks, management capabilities and container support using technologies like Apache Camel, CXF, ActiveMQ and Karaf.
Building an ML Platform with Ray and MLflowDatabricks
This document summarizes a talk on building an ML platform with Ray and MLflow. Ray is an open-source framework for distributed computing and machine learning. It provides libraries like Ray Tune for hyperparameter tuning and Ray Serve for model serving. MLflow is a tool for managing the machine learning lifecycle including tracking experiments, managing models, and deploying models. The talk demonstrates how to build an end-to-end ML platform by integrating Ray and MLflow for distributed training, hyperparameter tuning, model tracking, and low-latency serving.
System Integration with Akka and Apache Camelkrasserm
This document summarizes the Apache Camel integration framework and how it can be used with Akka actors. Camel provides a domain-specific language and components for integration patterns and protocols. Akka actors handle asynchronous message processing and can be used as Camel consumers and producers through Akka-Camel integration. Consumer actors receive messages from Camel endpoints, while producer actors send messages to endpoints. Actor components allow actors to be used directly in Camel routes.
MSc Enterprise Systems Development Guest Lecture at UniS (2/12/09)Daniel Bryant
A guest lecture I presented to MSc Level Enterprise Systems Development students within the Department of Computing at the University of Surrey. This was a very similar presentation to the L2 lecture delivered the week earlier, but also included more advanced material.
Sling Models Using Sightly and JSP by Deepak KhetawatAEM HUB
This document discusses using Sling Models with Sightly and JSP templates in AEM. It provides an overview of Sling Models, including their purpose, design goals, and key annotations. It also describes the standard injectors available in Sling Models and how to create custom injectors. The document outlines how to add Sling Model dependencies and use Sling Models within JSP and Sightly templates, including code examples. It concludes with a demonstration of Sling Models in action and information for appendix materials and questions.
Spring is a lightweight, open-source application framework for Java. It uses dependency injection (DI) and inversion of control (IOC) to decouple application components. Spring's features include AOP, transaction management, JDBC support, and integration with various web frameworks like Struts and MVC. It supports DI through constructor injection and setter injection. Spring applications typically use XML configuration files to wire application components together.
This document discusses Sling Models, which provide a simplified way to adapt Sling resources into domain objects in AEM. Some key points:
- Sling Models allow resources to be adapted to POJOs with minimal code using annotations like @Model and @Inject. This is cleaner than previous "adapter factory" approaches.
- Common use cases like injecting resource properties, child resources, services and more are supported out of the box via standard injectors.
- Sling Models are pluggable, so custom injectors can be added to inject non-standard dependencies.
- They allow resources and requests to be adapted to either classes or interfaces, keeping domain objects simple POJOs.
The document discusses Java AWT event handling and graphics. It covers key concepts like events, event classes, event handling process, commonly used event listeners and adapter classes. It also covers AWT containers, layout managers, menu classes, graphics classes and how to work with frames and graphics in Java. The document is intended to teach programming in Java and is part of a larger unit on AWT.
This document discusses different options for navigating between task flows in an ADF application, including stack, network, hybrid, dashboard, and parallel navigation. It explains how each approach impacts memory usage, performance, and the user experience. Key factors like how task flows call or embed each other, and whether state is maintained or restored between flows, determine the tradeoffs of each approach. The document provides guidance to help developers choose a navigation strategy based on their specific requirements.
This document discusses Sling Models in AEM, including what they are, why they are useful, how to use them, and examples of Sling Model annotations. Sling Models allow mapping of Sling objects like resources and requests to plain Java objects using annotations. They reduce coding efforts and make code more maintainable by avoiding redundant code. The document covers the necessary dependencies, common annotations like @Model, @Inject, @Optional, and examples of injecting resources, child resources, and retrieving values from the request.
The document describes E-GEN iCAN, a tool for collecting, analyzing, and navigating production data in schedulers and z/OS environments. It provides an overview of the tool's interface and features, including its collectors, user interface, search engine, audit functionality, and client-server architecture. Use cases demonstrate how the tool can be used to generate run books, perform impact analysis, and enable quality assurance processes.
This document provides an overview of enterprise integration patterns (EIPs) and how they are implemented using Apache Camel and Project Fuji frameworks. It discusses core EIP principles like asynchronous messaging for integration. It also describes various EIP implementations like content-based routing, dead letter channels, and message transformation patterns. Code examples are shown using the Java and Spring DSLs for Apache Camel and the DSL and web UI for Project Fuji.
Real world #microservices with Apache Camel, Fabric8, and OpenShiftChristian Posta
What are, or aren't, microservices?
There's a lot of hype and buzz, but microservices emerged organically vs how some of the other distributed architectural styles were "handed down to us", so I believe there's some good things once you cut through the hype. In this talk I discussed what are and are NOT microservices, introduced some concepts, and discussed some concrete open-source libraries and frameworks that can help you develop and manage microservice style deployments.
Real-world #microservices with Apache Camel, Fabric8, and OpenShiftChristian Posta
What are and aren't microservices?
Microservices is a validation of the open-source approach to integration and service implementation and a rebuff of the committee-driven SOA approach. In this
The document discusses Apache Camel, an open source framework for integrating applications and building messaging endpoints. It provides an overview of Camel's capabilities including its lightweight nature, large number of components, support for various data formats, and use of Domain Specific Languages. Basic examples are shown using XML and Java DSLs. Key components, data formats, and Enterprise Integration Patterns supported by Camel are listed. Pros include its flexibility and large community, while documentation is listed as a con. Overall the document serves as an introduction to Apache Camel, outlining its main features and providing simple code examples.
Alfresco Business Reporting - Tech Talk Live 20130501Tjarda Peelen
This is the Slide Deck used in Alfresco's Tech Talk Live, May 1, 2013. It featured my Alfresco add-on: Alfresco Business Reporting. The purpose is to the technical 'why' and 'how' of the add-on module, the challenge faced and he solutions designed.
WebNet Conference 2012 - Designing complex applications using html5 and knock...Fabio Franzini
This document provides an overview of designing complex applications using HTML5 and KnockoutJS. It discusses HTML5 and why it is useful, introduces JavaScript and frameworks like KnockoutJS and SammyJS that help manage complexity. It also summarizes several JavaScript libraries and patterns including the module pattern, revealing module pattern, and MV* patterns. Specific libraries and frameworks discussed include RequireJS, AmplifyJS, UnderscoreJS, and LINQ.js. The document concludes with a brief mention of server-side tools like ScriptSharp.
This document provides an overview of ASP.NET MVC including its history, the MVC pattern, controllers, views, routing, and Razor views. It discusses the Model-View-Controller components, controller actions, action results, and action filters. It also covers view helpers, layouts, sections, and Razor syntax features.
Julien Simon "Scaling ML from 0 to millions of users"Fwdays
This document discusses scaling machine learning models from a single instance to millions of users. It begins by describing starting with a model on a local machine and then deploying it on a single EC2 instance. It notes the issues that arise with this approach as needs increase. It then discusses options for scaling to multiple instances, Docker clusters using ECS/EKS, and the fully managed SageMaker service. SageMaker is argued to require minimal effort for infrastructure and deployment compared to the other options as it scales models easily and focuses solely on machine learning tasks.
This document provides an overview of integrating microservices with Apache Camel and JBoss Fuse. It introduces Apache Camel as a lightweight integration library that uses enterprise integration patterns and domain-specific languages to define integration "flows" and "routes". It describes how Camel supports features like dynamic routing, REST APIs, backpressure, load balancing, and circuit breakers that are useful for building microservices. The document also introduces JBoss Fuse as a development and runtime platform for microservices that provides tooling, frameworks, management capabilities and container support using technologies like Apache Camel, CXF, ActiveMQ and Karaf.
Building an ML Platform with Ray and MLflowDatabricks
This document summarizes a talk on building an ML platform with Ray and MLflow. Ray is an open-source framework for distributed computing and machine learning. It provides libraries like Ray Tune for hyperparameter tuning and Ray Serve for model serving. MLflow is a tool for managing the machine learning lifecycle including tracking experiments, managing models, and deploying models. The talk demonstrates how to build an end-to-end ML platform by integrating Ray and MLflow for distributed training, hyperparameter tuning, model tracking, and low-latency serving.
System Integration with Akka and Apache Camelkrasserm
This document summarizes the Apache Camel integration framework and how it can be used with Akka actors. Camel provides a domain-specific language and components for integration patterns and protocols. Akka actors handle asynchronous message processing and can be used as Camel consumers and producers through Akka-Camel integration. Consumer actors receive messages from Camel endpoints, while producer actors send messages to endpoints. Actor components allow actors to be used directly in Camel routes.
Microservices for java architects it-symposium-2015-09-15Derek Ashmore
This document provides an overview of microservices for Java architects by Derek Ashmore. It begins by introducing Ashmore and his background. The document then discusses what microservices are, how they differ from traditional monolithic architectures, and considerations for designing microservices like service boundaries, handling failures, ensuring data integrity and performance. It also covers packaging and deployment options for microservices like Spring Boot and Docker. Finally, it addresses some common misconceptions about microservices and provides additional resources for further reading.
This document discusses how to scale Mule applications globally through techniques like parallel processing, asynchronous tasks, orchestration, messaging backbones, clustering, and load balancing. It describes common problems with performance, integration, security, and transactions in large enterprises and how Mule addresses these through features such as transactions, computation optimization, identifying bottlenecks, and using external services like databases and messaging infrastructure.
Analytics Metrics delivery and ML Feature visualization: Evolution of Data Pl...Chester Chen
GoPro’s camera, drone, mobile devices as well as web, desktop applications are generating billions of event logs. The analytics metrics and insights that inform product, engineering, and marketing team decisions need to be distributed quickly and efficiently. We need to visualize the metrics to find the trends or anomalies.
While trying to building up the features store for machine learning, we need to visualize the features, Google Facets is an excellent project for visualizing features. But can we visualize larger feature dataset?
These are issues we encounter at GoPro as part of the data platform evolution. In this talk, we will discuss few of the progress we made at GoPro. We will talk about how to use Slack + Plot.ly to delivery analytics metrics and visualization. And we will also discuss our work to visualize large feature set using Google Facets with Apache Spark.
This document discusses Eclipse 4.0 and the e4 project. It provides an overview of why e4 was created, including to innovate Eclipse and prepare it for the web. It describes the key aspects of e4, including the modeled workbench, dependency injection, declarative styling using CSS, and a compatibility layer for Eclipse 3.x plugins. The presentation concludes by discussing where to learn more about e4.
Apache Samza is a stream processing framework that provides high-level APIs and powerful stream processing capabilities. It is used by many large companies for real-time stream processing. The document discusses Samza's stream processing architecture at LinkedIn, how it scales to process billions of messages per day across thousands of machines, and new features around faster onboarding, powerful APIs including Apache Beam support, easier development through high-level APIs and tables, and better operability in YARN and standalone clusters.
Impact 2014 - IIB - selecting the right transformation optionAndrew Coleman
The document discusses different options for transforming messages in IBM Integration Bus, including mapping, XSLT, ESQL, Java, PHP, and .NET. It provides an overview of each technology's functionality, strengths, weaknesses, and how they can be used for transformation in the bus. The major transformation technologies - mapping, XSLT, ESQL, and compute nodes using Java - are described in more detail, outlining their performance, features, ease of use, portability, and maintenance characteristics. Mapping provides a graphical drag-and-drop interface using XPath, while XSLT uses the XSLT language. ESQL supports SQL-like queries and calling Java methods. Compute nodes allow calling static Java methods.
A machine learning and data science pipeline for real companiesDataWorks Summit
Comcast is one of the largest cable and telecommunications providers in the country built on decades of mergers, acquisitions, and subscriber growth. The success of our company depends on keeping our customers happy and how quickly we can pivot with changing trends and new technologies. Data abounds within our internal data centers and edge networks as well as both the private and public cloud across multiple vendors.
Within such an environment and given such challenges, how do we get AI, machine learning, and data science platforms built so our company can respond to the market, predict our customers’ needs and create new revenue generating products that delight our customers? If you don’t happen to be our friends and colleagues at Google, Facebook, and Amazon, what are technologies, strategies, and toolkits you can employ to bring together disparate data sets and quickly get them into the hands of your data scientists and then into your own production systems for use by your customers and business partners?
We’ll explore our journey and evolution and look at specific technologies and decisions that have gotten us to where we are today and demo how our platform works.
Speaker
Ray Harrison, Comcast, Enterprise Architect
Prashant Khanolkar, Comcast, Principal Architect Big Data
This document contains only attribution lines crediting various photographers for their photos and no other text. It seems to be a collection of photo credits but without any images included. The document ends by asking if the reader is inspired, possibly to make their own photo or image collection.
This document contains a list of photo credits attributed to various photographers. There are over 30 different photographers credited with individual photos. The document does not provide any additional context or details about the photos themselves. It simply lists photographer names and photo credits.
Our society is hugely information based – we create and manage products and services which are dependent on the right person having the right information at the right time. In other words, information-related disasters are an increasingly real threat to organisations today.
There are several kinds of 'information disasters' - some are caused by the wrong information, others by out-of-date information and some quite simply by too much information.
OSGi is a module system for Java that handles lifecycles of individual bundles, provides class loading isolation between bundles, and manages dependencies and versioning. It treats each deployable unit as a bundle, which is a JAR file with additional metadata. OSGi allows restricting visibility of classes on a per-bundle basis and loading classes from different bundles through separate classloaders. Bundles in OSGi go through lifecycle states like installation, resolution, starting, stopping, and updating. OSGi also supports a service registry for bundles to publish and discover services. Popular implementations of OSGi include Apache Felix and Eclipse Equinox.
The document outlines requirements for aggregating stock quotes from three separate parties - Reuters, Nasdaq, and TickerTech. Reuters will send FTP files with quotes in CSV format. Nasdaq will call a web service to transmit quotes in XML format. TickerTech has a public HTTP service that returns quotes in JSON format and needs to be polled. The aggregated quotes need to be sent to a backend trading application and website in near real-time.
The document discusses FuseSource products including Fuse Message Broker, Fuse Mediation Router, Fuse Services Framework, and Fuse ESB. It provides information on the presenter, Billy Sjöberg, and his experience. The presentation includes demonstrations of Camel, CXF, and ActiveMQ integration as well as OSGi basics and Camel in ServiceMix.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
1. REDPILL LINPRO
SWAT
Competence Gathering #1 Apache Camel
April 2011 introduction
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
2. Agenda
Background
EIP
Architecture from 10,000 ft
Endpoints & components
Programming model
Hiding the integration API from your code
Error handling
Type converters
Deployment
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3. Background
Started as a subproject to ActiveMQ
Now one of the top Apache projects
Implementation of the EIP patterns
Framework for declaring routing logic
NOT a fullblown runtime, such as an ESB.
… but has the same characteristics
Reuses Spring concepts such as Templates, DI, registries,
contexts etc..
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
4. Enterprise Integration Patterns
(EIP)
”Pipe and filter” stateless flows
The de facto bible when it comes to the messaging
integration style
EIP is the basis for all types of flow-based integration
frameworks (i.e. Camel, Spring Integration, Jboss ESB,
Mule)
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
6. A Camel EIP example
Queue
Papers
Split on each Route on body Queue
Queue
lineitem Pencils
purchaseOrder
File dir
/invalid
from("jms:queue:purchaseOrder?concurrentConsumers=5")
.split().xpath("//lineItem")
.choice()
.when(body().contains("Pen")) .to("jms:queue:Pencils")
.when(body().contains("Paper")).to("jms:queue:Papers")
.otherwise().to("file:target/messages/invalid");
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
7. 10,000 ft architecture
CamelContext - Runtime "engine", similar to a SpringContext
Routes - Your DSL/XML declared flows
Components - Physical connectivity factories to Endpoints, i.e to()/from()
Processors - Implements the Processor interface (process() method)
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
8. Components and endpoints
> 100 components jms:myQueue?concurrentConsumers=5&username=Billy
Component Path Options
Separate JAR's
The usual suspects...
File / JMS / RMI / WS / Http / DB
+ a lot more
SEDA, Direct, MINA, XMPP,
WebSockets, Twitter...
Components are bound to URI schemes
..which are then interpreted as Endpoints
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
9. Message Exchanges
Context for messages
Exchange ID – Unique id
MEP – InOnly/InOut Enum
Exception – Contains eventual runtime
exception
Properties – Meta-Data with a lifecycle
of the complete exchange
Message – In/Out used in processors
and request/reply
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
10. Programming model
Java "DSL" from("file:data/orders")
(chained methods) .split.xpath("//order")
.to("jms:queue:order");
Declarative XML <route>
(NS support) <from uri="file:data/orders"/>
<split>
<xpath>//order</xpath>
<to uri="jms:queue:order"/>
</split>
</route>
- Scala and Groovy alternatives...
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
11. Adding the routes, Java style
public class MyRoutes extends RouteBuilder{
@Override
public void configure() throws Exception {
from("file:/orders").to("jms:/orders");
from("file:/payments").to("jms/payments");
}
}
camelContext.addRoutes(new MyRoutes());
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
12. Adding the routes, Spring /
Blueprint style
<camelContext xmlns="http://camel.apache.org/schema/spring">
<route>
<from uri="file:/orders"/>
<to uri="jms:/orders"/>
</route>
<route>
<from uri="file:/payments"/>
<to uri="jms:/orders"/>
</route>
</camelContext>
Bootstraps the context as Spring starts
Main, servlet listener, camel included Main class etc
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
13. Loading Java Routes from XML
Mix'n match between XML/Java
Consistent concept throughout the framework
<camelContext xmlns="http://camel.apache.org/schema/spring">
<packageScan>
<package>com.rl.routes</package>
<excludes>**.*Excluded*</excludes>
<includes>**.*</includes>
</packageScan>
</camelContext>
Irrespective of the language choice, the routes will be
the same as it's only instructions to Camel
Means that cross-functionality such as visualization etc
works across the languages
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
14. Processors
Simple way to add custom logic in a route
Implements the Processor interface
Quick and dirty way, define your own anonymous impl inline
from("file:/payments")
.process(new Processor(){
public void process(Exchange exchng) throws Exception {
//business logic on exchange here
}
})
.to("jms:payments");
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
15. Service activator pattern
Instead of implementing the Processor intf
Reference service beans instead
Flexible, less Camel API smell
Camel can guess method based on message
type/parameters, annotations or method-ref
Can also reference by class type instead of registered
beans
from("file:/payments")
.beanRef("paymentService")
.to("jms/payments");
@Service
class PaymentService{
public PaymentAck conductPayment(String payment){...
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
16. The Registry
public interface Registry {
Object lookup(String name);
<T> T lookup(String name, Class<T> type);
<T> Map<String, T> lookupByType(Class<T> type);
}
Strategy interface for bean lookups
Used internally, i.e for finding a TransactionManager impl
As well as from your flows, using beanRef(”myBean”)
Impl delegates to SpringContext, CDI BeanManager, Guice,
OSGi etc...
camelContext.setRegistry(myRegistry)
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
17. Payload type conversion
from("file://inbox")
.convertBodyTo(String.class, "UTF-8")
.to("jms:inbox");
Camel often automatically tries to convert message payload to
method param based on registered converters
If not, use .convertBodyTo(clazz) from flow to invoke type
converter explicitly
Could be used where default type would not be the best fit
I.e. explicitly wanting JMS TextMessage over ByteMessage
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
18. Writing type converters
@Converter
public final class IOConverter {
@Converter
public static InputStream toInputStream(URL url) throws IOException {
return url.openStream();
}
}
META-INF/services/org/apache/camel/TypeConverter
com.rl.common.typeconverters.IOConverter
com.rl.<customer>.typeconverters.MyConverter
....
Or in runtime using..:
context.getTypeConverterRegistry().addTypeConverter(from, to, converter);
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
19. CamelProxy – Hiding Camel
from clients
Same concept as i.e. Spring Remoting
Camel automatically creates proxy implementations of a given
interface
DI-wire your proxy to the client
<camelContext xmlns="http://camel.apache.org/schema/spring">
<proxy id="paymentService" serviceInterface="se.rl.IPaymentService"
serviceUrl="direct:payments"/>
<route>
<from uri="direct:payments"/>
<to uri="...."/>
......
</route>
</camelContext>
<b:bean id="paymentClient" class="se.rl.banking.PaymentClient">
<b:property name="paymentSvc" ref="paymentService"/>
</b:bean>
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
20. Error handling
Thrown exceptions → Exchange.exception
Typically technical exceptions
Camel Error handling by default only kicks in when
exchange.getException() != null
Error handling is declarative and very flexible
But you should test your assumptions!
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
21. Error handlers
Default Error handling:
No redelivery
Exceptions are propagated back to the caller / incoming endpoint
DefaultErrorHandler Default if none specified
<retryable>
DeadLetterChannel Implements DLQ pattern. Redirect message.
<retryable> Also supports rolling back to original message
TransactionErrorHandler Only used for transactions
<retryable>
NoErrorHandler Dummy
LoggingErrorHandler Logging
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
22. Error handler features
errorHandler(defaultErrorHandler()
.maximumRedeliveries(2)
.redeliveryDelay(1000)
.retryAttemptedLogLevel(LoggingLevel.WARN));
from("seda:queue.inbox")
.beanRef("orderService", "validate")
.beanRef("orderService", "enrich")
.log("Received order ${body}")
.to("mock:queue.order");
Redelivery policies Specify retries, exponential backoff etc.
Redelivery will be on the exception origin,
NOT from the start of the route
Scope Context or on a route basis
Exception policies (onException(E)) Specific policies for particular exceptions
onWhen Even more fine-grained control. I.e check
status code on Http exceptions.
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
23. Exception policies
onException(JmsException.class)
.handled(true)
.beanRef("errorFormatter");
from("jetty:http://0.0.0.0:80/orderservice")
.beanRef("orderTransformer")
.to("jms:queue:incomingOrders")
.beanRef("orderAckTransformer");
onException lets you provide granularity to exception handling
handled(true) instructs the incoming endpoint to not throw
exception back at caller
Basically an alternative route for i.e constructing an error reply
message, without it the consumer would get the actual
exception
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
24. Deployment options
Camel is only a framework, not a deployment server
WAR, Java standalone, JMS Provider, ServiceMix OSGI, in-
application
Think about what Spring did for web app environment
independence, Camel does the same for integration
solutions
Does not impose restrictions on deployment
environment!
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
25. Proposed deployment path
Camel as stand-alone app or deployed into Jetty/Tomcat
Good for PoC and getting to know the framework
Another option is to bundle Jetty inside your application (as in
demo)
Tomcat/Jetty
OrderRoutes.war
camel- camel- camel-
core file cxf
P2pRoutes.war
camel- camel- camel-
core file cxf
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
26. For transactional use-cases and messaging, consider deploying
to your standard Java EE container (JBoss, Glassfish,
Weblogic, Websphere)
Java EE container
OrderRoutes.war
camel- camel- camel-
core jms jdbc
P2pRoutes.war
camel- camel- camel-
core jms jdbc
JMS / JPA /
JTA
JCA adapters DataSources
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
27. To scale – go full OSGI, deploying to Fuse ESB/ServiceMix
Removes need to bundle Camel in application
Makes multi-versions at runtime possible
Extra features for route management etc..
Fuse ESB/ServiceMix
camel-core
1.0
OrderRoutes.jar
camel-jms 1.0
camel-jdbc
1.0
P2pRoutes.jar
camel-... x.x
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING
28. More info at
Camel Official site
http://camel.apache.org/
FuseSource webinars
http://fusesource.com/resources/video-archived-webinars/
Open Source SOA with Fuse
http://www.parleys.com/#sl=2&st=5&id=1577
And of course, the Camel In Action book!
PRODUCTS • CONSULTING • APPLICATION MANAGEMENT • IT OPERATIONS • SUPPORT • TRAINING